ML model to detect malicious use of TakeTwo crowdsourced labeling

### Background on the problem the feature will solve/improved user experience
As an open-source, data crowdsourced solution, there is potential for malicious use/contributions

### Describe the solution you'd like
Develop an ML model(s) that detects malicious use such as:
- seeking to spam
- alter what is considered by racist, by making offensive racist terms seem less racist or identifying non-racist, benign terms as racist with the intent of making the api useless (by classifying everything as racist)
-
### Tasks
Description of the development tasks needed to complete this issue, including tests,

### Acceptance Criteria
Standards we believe this issue must reach to be considered complete and ready for a pull request. E.g precisely all the user should be able to do with this update, performance requirements, security requirements, etc as appropriate.

未指定任何檔案、進入點、測試或驗收標準。先調查儲存庫中的 Jupyter notebooks 和現有的 data-science workflow，然後在實作之前定義惡意使用訊號、評估資料以及可衡量的完成標準。

由索引模型根據 Issue 內容生成。